computes a jacobian of implicit non-linear diffusion contributions to time evolution matrices at a point U
.
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Functions | |
function sm = | fv_frechet_operators_diff_implicit_gradient2 (model, model_data, U, NU_ind) |
computes a jacobian of implicit non-linear diffusion contributions to time evolution matrices at a point U . More... | |
computes a jacobian of implicit non-linear diffusion contributions to time evolution matrices at a point U
.
Definition in file fv_frechet_operators_diff_implicit_gradient2.m.
function sm = fv_frechet_operators_diff_implicit_gradient2 | ( | model, | |
model_data, | |||
U, | |||
NU_ind | |||
) |
computes a jacobian of implicit non-linear diffusion contributions to time evolution matrices at a point U
.
function computing the jacobian in U
of the implicit diffusion contribution of \(L_I\) and \(b_I\) to the time evolution matrices for a finite volume time step \(L_I U^{k+1} = L_E U^k + b_E + b_I\). With the help of the returned Jacobian L_I_diff_jac
the Frechet derivative \(DL_I ({U})\) is approximated.
dt
increase in model
before evaluating the data functions.Note: This only works when diffusivity is averaged on edge points by arithmetic mean, adapt the function, if you want to use geometric or harmonic mean functions.
model | model |
model_data | model data |
U | U |
NU_ind | NU ind |
sm | sm |
L_I_diff_jac | a sparse matrix with jacobian of diffusion contributions to \(L_I\). |
bdir_I_diff_jac | and offset vector containing the Dirichlet value contributions of the diffusion parts. |
diffusivity_derivative_ptr —
diffusivity derivative ptr diffusivity_ptr —
diffusivity ptrsn —
sn sm —
sm si —
si sj —
sj svals —
svals Definition at line 17 of file fv_frechet_operators_diff_implicit_gradient2.m.